Statistics Toolbox provides multiple ways to explore data: statistical plotting with interactive graphics, algorithms for cluster analysis, and descriptive statistics for large data sets.
Statistics Toolbox includes graphs and charts to visually explore your data. The toolbox augments MATLAB® plot types with probability plots, box plots, histograms, scatter histograms, 3D histograms, control charts, and quantile-quantile plots. The toolbox also includes specialized plots for multivariate analysis, including dendrograms, biplots, parallel coordinate charts, and Andrews plots.
Visualizing Multivariate Data (Example)
How to visualize multivariate data using various statistical plots.
Modelling Data with the Generalized Extreme Value Distribution (Example)
How to fit the generalized extreme value distribution using maximum likelihood estimation.
Descriptive statistics enable you to understand and describe potentially large sets of data quickly. Statistics Toolbox includes functions for calculating:
These functions help you summarize values in a data sample using a few highly relevant numbers.
In some cases, estimating summary statistics using parametric methods is not possible. To deal with these cases, Statistics Toolbox provides resampling techniques, including: